#Inference

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#Inference Reel by @rebuildtoday (verified account) - In a conversation on C-SPAN, neuroscientist and educator Dr. Jared Cooney Horvath offered a striking critique of how technology is reshaping what we c
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@rebuildtoday
In a conversation on C-SPAN, neuroscientist and educator Dr. Jared Cooney Horvath offered a striking critique of how technology is reshaping what we call “learning” in schools. He describes how reading comprehension tests—once designed to assess deep thinking and inference—are being reduced to surface-level skimming to match the way children interact with screens . And it’s not just a change in style. It’s a shift in cognitive development. A global OECD study spanning 80 countries found that students who use digital devices for more than five hours a day in school perform significantly worse—by two-thirds of a standard deviation—than peers with limited tech exposure . The more pervasive the tech use, the sharper the decline. Developmental psychologists like Maryanne Wolf (author of Reader, Come Home) have warned for years that digital skimming rewires the brain away from deep reading and critical analysis—undermining the very skills education is meant to build. What Dr. Horvath underscores isn’t an anti-tech sentiment. It’s a plea not to mistake convenience for cognitive growth. As he puts it, redefining education to suit the tool isn’t progress. It’s surrender. And as US state-level data shows, the correlation is hard to ignore: standardized performance tends to decline right after widescale 1:1 tech adoption begins. In an age when screens are everywhere, his message is clear: our kids don’t need more tech in the classroom. They need better thinking spaces—offline, slow, and built for depth. —— We share content that fosters a deep sense of human connection. Tap the link in bio to join the Rebuild newsletter - @rebuildtoday —— Speaker: @jared.cooney.horvath Source: @cspan
#Inference Reel by @vaibhavsisinty (verified account) - Nvidia just killed competition.

It just absorbed their only real competitor without an "acquisition."

 $20B licensing deal = all the tech, all the t
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@vaibhavsisinty
Nvidia just killed competition. It just absorbed their only real competitor without an “acquisition.” $20B licensing deal = all the tech, all the talent, none of the antitrust drama. The $255B inference market is theirs.
#Inference Reel by @centerofainews - RAM prices are climbing alongside the surge in AI.

As models scale and data centers continue to grow, demand for memory keeps accelerating. It's no
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@centerofainews
RAM prices are climbing alongside the surge in AI. As models scale and data centers continue to grow, demand for memory keeps accelerating. It’s not just about GPUs anymore—RAM capacity and bandwidth are now just as critical for performance, cost efficiency, and scalability. Every training run, every inference request, every real-time system relies heavily on memory. When demand rises faster than supply can keep up, pricing pressure builds fast. This isn’t a temporary spike. It’s a sign of deeper infrastructure strain. In the AI economy, memory isn’t secondary—it’s strategic. Follow @centerofainews for more ai content! #RAM #RAMPrices #AI #ArtificialIntelligence #semiconductors
#Inference Reel by @msdeannajump (verified account) - The toy sack has vanished… and the Inference Detectives need backup. 🕵️‍♂️🧐
Think your class can crack the case?
Drop TOYS and I'll send the mystery
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MS
@msdeannajump
The toy sack has vanished… and the Inference Detectives need backup. 🕵️‍♂️🧐 Think your class can crack the case? Drop TOYS and I’ll send the mystery to your inbox! 🎁🔍 #firstgrade #kindergarten #classroomideas #teacherideas #homeschool #classroomactivities
#Inference Reel by @quantmaxxing - Quants come from a wide range of STEM backgrounds because quantitative finance demands people who can model complex systems, work with uncertainty, an
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@quantmaxxing
Quants come from a wide range of STEM backgrounds because quantitative finance demands people who can model complex systems, work with uncertainty, and build high-performance software. The most common backgrounds include: • Mathematics (probability, stochastic calculus, optimization, PDEs) • Statistics (inference, regression, time series, Bayesian modeling) • Physics (signal extraction, dynamical systems, modeling noisy real-world processes) • Computer Science (algorithms, machine learning, distributed systems, low-latency engineering) • Electrical/Computer Engineering (hardware-level optimization, FPGA/embedded systems, systems design) • Applied Mathematics (numerical methods, simulation, Monte Carlo, scientific computing) • Data Science / Machine Learning (pattern recognition, predictive modeling, feature engineering) • Operations Research (optimization, decision theory, control systems)
#Inference Reel by @catgpt.daily - RAM prices are rising with the momentum of AI.

As models grow larger and data centers expand, memory demand keeps stacking up. It's no longer just ab
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@catgpt.daily
RAM prices are rising with the momentum of AI. As models grow larger and data centers expand, memory demand keeps stacking up. It’s no longer just about GPUs RAM capacity and bandwidth are becoming just as critical to performance, cost, and scalability. Every training run, every inference request, every real-time system pulls on memory. And when that demand compounds faster than supply can respond, pricing pressure builds quickly. This isn’t a short-term fluctuation. It’s infrastructure strain In the AI economy, memory isn’t secondary it’s strategic. Follow for more @catgpt.daily #RAM #RAMPrices #AI #ArtificialIntelligence #Semiconductors
#Inference Reel by @dailyaiinformation - RAM prices are rising with the momentum of AI.

As models grow larger and data centers expand, memory demand keeps stacking up. It's no longer just ab
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@dailyaiinformation
RAM prices are rising with the momentum of AI. As models grow larger and data centers expand, memory demand keeps stacking up. It’s no longer just about GPUs RAM capacity and bandwidth are becoming just as critical to performance, cost, and scalability. Every training run, every inference request, every real-time system pulls on memory. And when that demand compounds faster than supply can respond, pricing pressure builds quickly. This isn’t a short-term fluctuation. It’s infrastructure strain In the AI economy, memory isn’t secondary it’s strategic. Follow for more @dailyaiinformation @theplaceforai @whereyoulearnai #RAM #RAMPrices #AI #ArtificialIntelligence #Semiconductors #TechMarkets #DataCenters #CloudInfrastructure #AIInfrastructure #FutureOfTech
#Inference Reel by @unfoldedai - RAM prices are rising with the momentum of AI.

As models grow larger and data centers expand, memory demand keeps stacking up. It's no longer just ab
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UN
@unfoldedai
RAM prices are rising with the momentum of AI. As models grow larger and data centers expand, memory demand keeps stacking up. It’s no longer just about GPUs RAM capacity and bandwidth are becoming just as critical to performance, cost, and scalability. Every training run, every inference request, every real-time system pulls on memory. And when that demand compounds faster than supply can respond, pricing pressure builds quickly. This isn’t a short-term fluctuation. It’s infrastructure strain In the AI economy, memory isn’t secondary it’s strategic. Follow for more @unfoldedai #RAM #RAMPrices #AI #ArtificialIntelligence #Semiconductors
#Inference Reel by @dailyaiinformation - RAM is turning into the silent bottleneck of the AI era.

As models expand and inference runs nonstop, memory demand is compounding. It's not just abo
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DA
@dailyaiinformation
RAM is turning into the silent bottleneck of the AI era. As models expand and inference runs nonstop, memory demand is compounding. It’s not just about faster chips anymore it’s about how much data you can hold and move at once. This isn’t a minor constraint. It’s structural In AI, memory defines the edge. Follow for more @dailyaiinformation #RAM #AI #ArtificialIntelligence #TechTrends #Semiconductors #Compute #DataCenters #CloudInfrastructure #AIStack #FutureOfTech
#Inference Reel by @hooverinstitution (verified account) - Science relies on inductive and abductive inference. Mathematics alone yields deductive certainty. Stephen C. Meyer makes this distinction on the late
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@hooverinstitution
Science relies on inductive and abductive inference. Mathematics alone yields deductive certainty. Stephen C. Meyer makes this distinction on the latest episode of Uncommon Knowledge with Peter Robinson. Watch it at the @HooverInstitution link in bio.
#Inference Reel by @red_hat (verified account) - Ever wonder what the 'v' in vLLM stands for? 💡 Chris Wright and Nick Hill explain how "virtual" memory and PagedAttention make AI inference more effi
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@red_hat
Ever wonder what the 'v' in vLLM stands for? 💡 Chris Wright and Nick Hill explain how "virtual" memory and PagedAttention make AI inference more efficient by solving GPU memory fragmentation in the latest episode of Technically Speaking. 🔗 Link in bio.
#Inference Reel by @rowancheung (verified account) - South Korean startup FuriosaAI is emerging as a potential challenger to Nvidia in the AI chip market. 

Founded in 2017 by former Samsung engineer Jun
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@rowancheung
South Korean startup FuriosaAI is emerging as a potential challenger to Nvidia in the AI chip market. Founded in 2017 by former Samsung engineer June Paik, the company develops neural processing units designed specifically for AI inference—running models after they’re trained. At Stanford’s Hot Chips conference, Furiosa demonstrated their RNGD chip running Meta’s Llama model with more than twice the power efficiency of Nvidia’s hardware. The company, now valued at nearly $700 million, declined an acquisition offer from Meta last year. OpenAI and LG have both tested the chips, reporting strong performance. Mass production of the RNGD chip begins this month. #ai #technology #nvidia #semiconductor #business

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